Prediction of single-track forming quality in laser melting deposition of Al-Mg-Sc-Zr alloy

被引：0

作者：

Xiao G. ^{[1
,2
,3
]}

Li W. ^{[1
]}

Xie L. ^{[1
]}

Lu C. ^{[4
]}

Liu X. ^{[1
,4
]}

Zhu B. ^{[1
,4
]}

Yang Q. ^{[3
]}

机构：

[1] College of Mechanical and Electrical Engineering, Hunan University of Science and Technology, Xiangtan

[2] Jiangxi Copper Technology Research Institute Co., Ltd., Nanchang

[3] College of Mechanical and Vehicle Engineering, Hunan University, Changsha

[4] College of Materials Science and Engineering, Guangdong Ocean University, Yangjiang

来源：

Zhongguo Youse Jinshu Xuebao/Chinese Journal of Nonferrous Metals | 2024年 / 34卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Al-Mg-Sc-Zr alloy; laser melting deposition; melting track quality; neural network; porosity rate;

D O I：

10.11817/j.ysxb.1004.0609.2023-44626

中图分类号：

学科分类号：

摘要：

The influence of laser melting deposition (LMD) process parameters on the forming quality of a single-track Al-Mg-Sc-Zr alloy was investigated. A BP neural network model and an improved PSO-BP neural network model were employed to predict the porosity rate of the formed track under different LMD parameters. The results demonstrate that the porosity rate firstly increases, then decreases, and finally increases with laser line energy density increasing. When the laser line energy density was 175 J/mm2, the porosity rate displays a minimum value, which is 1.38%. Under the same powder feeding rate, the width and depth of the track show a positive correlation with laser power, while the height and depth of the track illustrate a negative correlation with scanning speed. In contrast to the BP neural network model, the average absolute error of the improved PSO-BP neural network model is reduced by 29.69%, the average relative error of the improved PSO-BP neural network model is reduced by 19.42%, the mean square error of the improved PSO-BP neural network model is reduced by 19.02% and the correlation coefficient of the improved PSO-BP neural network model is improved by 63.44%. © 2024 Central South University of Technology. All rights reserved.

引用

页码：1010 / 1021

页数：11

共 34 条

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